Graph neural network based SAR automatic target recognition with human-in-the-loop

Bingyi Zhang; Sasindu Wijeratne; Rajgopal Kannan; Viktor Prasanna; Carl Busart

doi:10.1117/12.2663728

13 June 2023 Graph neural network based SAR automatic target recognition with human-in-the-loop

Bingyi Zhang, Sasindu Wijeratne, Rajgopal Kannan, Viktor Prasanna, Carl Busart

Proceedings Volume 12520, Algorithms for Synthetic Aperture Radar Imagery XXX; 125200J (2023) https://doi.org/10.1117/12.2663728
Event: SPIE Defense + Commercial Sensing, 2023, Orlando, Florida, United States

Abstract

Synthetic Aperture Radar (SAR) automatic target recognition (ATR) is a key technique for SAR image analysis in military activities. Accurate SAR ATR can promote command and decision-making. In this work, we propose a novel SAR ATR framework with human-in-the-loop. The framework consists of a Reinforcement Learning (RL) Agent, which is followed by a GNN-based classifier. The RL Agent is capable of learning from human feedback to identify the region of target (RoT) in the SAR image. The RoT is then used to construct the input graph for the GNN classifier to perform target classification. By learning from human feedback, the RL Agent can focus on the RoT and filter out irrelevant and distracting signals in the input SAR images. We evaluate the proposed framework on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset. The results show that incorporating human feedback can improve classification accuracy. By visualizing the results, we observe that the RL Agent can effectively reduce irrelevant SAR signals in the input SAR images after learning from human feedback.

Conference Presentation

Citation Download Citation

Bingyi Zhang, Sasindu Wijeratne, Rajgopal Kannan, Viktor Prasanna, and Carl Busart "Graph neural network based SAR automatic target recognition with human-in-the-loop", Proc. SPIE 12520, Algorithms for Synthetic Aperture Radar Imagery XXX, 125200J (13 June 2023); https://doi.org/10.1117/12.2663728

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available